ChatGPT: is it really that big a game changer for our lives and businesses?
AI technologies are being used to improve efficiency, enhance the customer experience, and gain valuable insights. One of the most significant developments in recent years has been the creation of large language models (LLMs). One of the most advanced LLMs currently available is the conversational AI system ChatGPT, based on GPT-3.5 from research and deployment company Open AI. Despite the rather primitive use of machine learning and statistical models (suggesting the most likely continuation or the answer to the question statistically), ChatGPT gained almost divine status among Internet users within a few weeks.
Words by: Jeremy Arancio & ChatGPT, Photos by Unsplash.com
Corporate Venture Builder Creative Dock, has been keeping an eye on the latest technological advancements to offer tailored solutions to its ventures. These solutions include a range of innovative services such as:
- Scoring for loans and financial transactions,
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- Evaluation of insurance risk by monitoring driving style,
- And increasing the efficiency of complex insurance case calculations (read more about it here).
This blog post explains ChatGPT fundamentals and how it is revolutionising all industries.
What are large language models?
Large language models are artificial intelligence systems that are trained on massive amounts of text data, such as books, articles, and web pages. The goal is to teach the model to understand human language and generate text similar in style and content to what a human would write.
The basis for the creation of the LLM is a complex field at the intersection of statistics, computer science, and language science — natural language processing (NLP).
What is natural language processing?
Natural Language Processing (NLP) is an advanced technology that enables machines to understand, interpret, and generate human language. It is a subfield of artificial intelligence that focuses on the interaction between computers and human language, allowing machines to process and analyse large amounts of textual data.
At its core, NLP relies on complex algorithms and statistical models that enable machines to identify patterns and relationships within language. This technology is used in various applications, including machine translation, sentiment analysis, speech recognition, and text-to-speech synthesis.
The potential of large language models for companies
The potential of systems working on large language models is vast. Companies can use these technologies to create more effective customer service chatbots to handle inquiries, improving customer satisfaction and loyalty. They can also be used to create personalised marketing content, improve content creation, and facilitate language translation.
What exactly is ChatGPT, how does it work, and what role can it play in the world?
A human brain
ChatGPT is a significant language model that has been trained on massive amounts of text data, such as books, articles, and web pages. This training allows ChatGPT to understand human language and generate text that is similar in style and content to what a human would write. In this sense, ChatGPT is like a human brain that has been trained to understand language and communicate through words.
ChatGPT uses a “memory” to generate text that contains all the information it has learned from its training data. This memory is like a vast library, with each book representing a different piece of information. When someone interacts with ChatGPT, it is like asking a librarian for information. The librarian goes to the library and retrieves the book that contains the relevant information. In the same way, ChatGPT retrieves the information it needs from its memory to generate a response.
A writing assistant
ChatGPT can be used for various applications, including chatbots, content creation, and language translation. In each of these applications, ChatGPT is like a writing assistant that helps you generate text that is similar in style and content to what a human would write. It can suggest sentence completions, provide synonyms, and even generate entire paragraphs.
Examples of ChatGPT best business use cases
Improved customer service
One of the most promising applications for ChatGPT is in customer service chatbots. Chatbots can help businesses handle many customer inquiries quickly and efficiently. However, traditional chatbots can be frustrating for customers to use, as they often provide generic responses that don’t fully address their questions. ChatGPT-powered chatbots, on the other hand, can generate more natural and personalised responses to the customer’s needs.
A retail company could use a ChatGPT-powered chatbot to assist customers with their purchasing decisions. When a customer asks for product recommendations, the chatbot can generate responses that consider the customer’s preferences and past purchasing history.
For example, the telecommunications company Vodafone uses ChatGPT to power its chatbot, TOBi. TOBi can handle a wide range of customer inquiries and provide helpful responses quickly. By using ChatGPT, Vodafone has been able to reduce customer wait times and improve customer satisfaction.
Cost-effective content creation
Another promising application for ChatGPT is in content creation. Generating high-quality content can be a time-consuming and costly process, but ChatGPT can help streamline this process. ChatGPT can generate articles, blog posts, and social media updates similar in style and content to what a human would write.
A marketing agency could use ChatGPT to generate social media updates for their clients. The agency could input key details about the client’s business and target audience, and ChatGPT could generate updates tailored to those specifications.
ChatGPT can also be used for language translation. By generating natural language text in multiple languages, ChatGPT can help companies communicate with customers and partners in different parts of the world.
An international business could use ChatGPT to translate emails and other communications between employees who speak different languages. ChatGPT could generate text in the target language that is similar in style and content to what a human would write.
For example, the software company HubSpot uses ChatGPT to generate translated content for its international customers. HubSpot inputs the English version of its content into the model, and ChatGPT generates translated versions of the content in multiple languages.
Enhanced marketing efforts
ChatGPT can also be used to enhance marketing efforts by providing personalised and engaging content to target audiences. With ChatGPT, businesses can generate social media posts, emails, and other marketing content tailored to their target customers' needs and interests.
For example, the media company Condé Nast uses ChatGPT to generate personalised emails for subscribers of its Wired magazine. The emails are generated based on the subscriber’s interests and past reading history, which makes them more relevant and engaging.
Challenges and limitations of ChatGPT in business applications
As with any new technology, there are concerns and limitations that need to be considered.
Data bias and fairness
Large language models are trained on vast amounts of text data, which can contain biases and prejudices that are present in society. This means that the model may reflect and amplify these biases in its output, potentially leading to discriminatory or unfair outcomes.
To address this concern, companies must be mindful of the data they use to train their models and take steps to ensure that their models are fair and unbiased. This may involve using diverse data sources, conducting regular audits to identify and mitigate bias, and building ethical guidelines into their development processes.
Privacy and security
Large language models can contain sensitive information, such as user data or confidential business information. This means that companies must take steps to ensure that their models are secure and protect user privacy.
To address this concern, companies must implement strong security measures, such as encryption and access controls, to protect their models and the data they contain. They must also be transparent with their users about how their data is being used, and provide options for users to control their data.
Large language models require significant amounts of computing power to train and operate, which can have a significant environmental impact. This is because the energy consumption associated with large language models contributes to climate change.
To address this concern, companies can reduce their models’ environmental impact, such as using renewable energy sources to power their servers or implementing more efficient computing practices.
Looking ahead: the future of large language models and ChatGPT
Large language models like ChatGPT have already revolutionized the field of natural language processing and artificial intelligence, and their potential for the future is even more exciting. As the technology advances and develops, we can expect to see even more innovative applications of these models.
From calculators to supercomputers
If we think of the development of large language models like a journey from calculators to supercomputers, we can see that we are still in the early stages of the journey. Just as early calculators were limited in their functionality and capacity, early language models were limited in their ability to generate high-quality text. However, as the technology continues to evolve, we can expect to see models with even greater capacity and functionality, capable of generating even more complex and nuanced text.
From learning to understanding
Another analogy for the future of large language models is that of a child’s development. Just as a child starts with basic language skills and gradually develops a deeper understanding of language, large language models are also evolving from basic learning to a deeper understanding of language. As these models continue to learn from vast amounts of text data, they will be able to generate more nuanced and sophisticated text that is closer to human-like understanding.
From tools to collaborators
Finally, we can think of the future of large language models as a shift from tools to collaborators. Just as early computers were primarily used to automate simple tasks, modern computers are now essential collaborators working alongside humans to achieve complex goals. In the same way, large language models like ChatGPT will become essential collaborators that work alongside humans to achieve more complex and nuanced language-related tasks.
Why businesses should consider using this technology
In conclusion, large language models like ChatGPT are already transforming how we interact and understand language. With their ability to generate human-like text and assist with a wide range of language-related tasks, they have the potential to revolutionise industries from healthcare to customer service.
However, it’s also important to acknowledge these models' potential limitations and concerns, from ethical considerations to data privacy. As the technology continues to evolve, it’s essential that we carefully consider these issues and use large language models responsibly and ethically. Considering these considerations, the future of large language models and ChatGPT is truly exciting. We can expect to see even more innovative business applications and developments in the years to come.
Looking for advice on how to exploit this technology for your business? Email us at firstname.lastname@example.org and get in touch with our AI specialist, Tomas Kovarik.